Research Area:  Internet of Things

Abstract:

Internet of things plays a major role in all the applications that are utilized for automating the environment. In this, the searching of devices in the larger network is a tedious process. Further, it became easier by defining the social relationship among the devices in the network. Social Internet of things is the combination of real-world network and multiple devices in the Internet of things. In social Internet of things, the user can access information globally at any place based on its ID. But, the accessing of this ID in the large database is difficult. Several works were carried out to locate the ID of the devices in the social Internet of things [SIoT]. Community and effective search-based algorithm is one of the methods for effective localization of devices in the social Internet of things as the conventional method for device localization. The Routing protocol for Low power and Lossy networks (RPL) able to increase lifetime of network with high packet loss. In existing, the localization and routing is performed separately. This problem is overcome with the proposed trust-based community nodes and optimized RPL in social Internet of things network. Here, the community is formed with the combination of high trust and low trust nodes of similar taste. These trusted node-based community formation helps to locate the trusty nodes in the transmission process. The dragon fly optimization is used to improve the RPL performance by selecting trusty nodes as next hop in the routing process. Due to the combination of trust community and optimized RPL, the lifetime and success rate of the data transmission is increased by 90% as compared to the existing preference-based device localization and traditional RPL protocol. The whole process is realized with the help of MATLAB R2018a in windows 10 environment. Therefore, the proposed trust community and optimized RPL is best for the trust-based data transmission in social Internet of things network by having high alive nodes of 90% and time delay of 30 s for hop localization.

Keywords:  

Author(s) Name:  S. Selvaraj,R. Thangarajan,M. Saravanan

Publisher name:  SPRINGER

DOI:  10.1007/978-981-16-1866-6_36

Volume Information:  pp 513-529

Paper Link:   https://link.springer.com/chapter/10.1007/978-981-16-1866-6_36